Governments, businesses, and individuals have a need for real-time situational awareness (SA) information for air, land, and water transportation purposes. For example, ship captains navigating arctic passages need real-time SA information to avoid moving icebergs, bad weather conditions, and other hazards. Likewise, planes, trains, trucks, and other transportation platforms can benefit from SA information.
Traditionally, SA is provided for defined geographic regions through a limited access and expensive network of communications, sensors, and command and control. SA information is extracted from a number of different data sources using a variety of communication devices and processed onboard a platform. Information is generally provided on a geographic basis with data sources differing between geographic regions. For example, a maritime vessel typically uses data from its onboard radar, “Aid-to-Navigation” radio reports, weather and environmental reports, etc. This data is not tailored to a specific vessel, may cover a broad geographic area, and, therefore, must be correlated, filtered, and interpolated by local platform staff to obtain relevant SA. Thus, SA is currently a skilled process, time consuming, and prone to error.
Moreover, current SA solutions cannot utilize a wide variety of data sources and cannot be readily adapted to consider new forms of data. For example, a vessel's SA does not currently take advantage of radar or other sensors from other cooperating vessels that could identify threats outside that vessel's detecting range, including intentional threats such as piracy, and environment threats such as ice formations. Further, such data could be used to monitor illegal activities, including drug smuggling, unlawful personal conveyance, and illegal fishing.
In addition, current SA solutions require specialized equipment and/or personnel and thus, are cost prohibitive for many users. Accordingly, improved SA systems and methods are needed.